library(plotly);
library(ggplot2);
library(ggfortify);
library(repr);
library(tidyr);
library(tsibble);
library(TSstudio);
library(anytime);
library(zoo);

Loading required package: ggplot2


Attaching package: 'plotly'


The following object is masked from 'package:ggplot2':

    last_plot


The following object is masked from 'package:stats':

    filter


The following object is masked from 'package:graphics':

    layout


Attaching package: 'tsibble'


The following objects are masked from 'package:base':

    intersect, setdiff, union


Attaching package: 'zoo'


The following object is masked from 'package:tsibble':

    index


The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

https://bolin.su.se/data/stockholm-historical-monthly-temperature-3?n=stockholm-historical-temps-monthly-3

Using adjusted

dataset = read.csv("dataset/stockholm_monthly_mean_temperature_1980_2020_adjust.csv", sep=';')
#rownames(dt) = as.integer(as.character(dt$year))
min_year = min(dataset$year)
max_year = max(dataset$year)
#dt = dt[,-1]
head(dataset)

train = ts(as.vector(t(as.matrix(dataset[,-1]))), start=c(1980, 1), end=c(max_year, 12), frequency =12)

dt_reshape <- data.frame(date=as.Date(as.yearmon(time(train))), temp=as.matrix(train))

#dt_reshape <- dataset %>% pivot_longer(cols=jan:dec, names_to = "month", values_to = "temp") %>%
#            unite(date, c(year, month))
#dt_reshape$date <- anydate(dt_reshape$date)
#print(dt_reshape)
head(dt_reshape)

options(repr.plot.width=15, repr.plot.height=8)
autoplot(train, xlab="Year", ylab="Temperature (°C)")+
    ggtitle("Monthly Mean Air Temperature (°C), Stockholm 1980-2020")+ 
    theme(plot.title = element_text(size = 35, face = "bold")) +
    guides(colour = guide_legend(title.hjust = 20))

fig <- plot_ly(dt_reshape, x = ~date, y = ~temp, type = 'scatter', mode = 'lines') %>%
        layout(title = 'Monthly Mean Air Temperature (°C)', plot_bgcolor = "#e5ecf6")
fig

boxplot(train~cycle(train), names=month.abb, xlab="", ylab="Temperature (°C)")

fig <- plot_ly(dt_reshape, y=~temp, type = "box")
fig
# https://stackoverflow.com/questions/40622933/rplotly-creating-multiple-boxplots-in-one-graph-as-a-group

For example, a root near 1 of the autoregressive polynomial suggests that the data should be differenced before fitting an ARMA model, whereas a root near 1 of the moving-average polynomial indicates that the data were overdifferenced.

	year	jan	feb	mar	apr	may	jun	jul	aug	sep	oct	nov	dec
	<int>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
1	1980	-4.7	-6.2	-3.1	4.8	7.8	15.6	16.8	14.6	12.8	5.7	0.0	-0.8
2	1981	-4.0	-2.7	-2.2	3.9	10.8	12.6	16.4	14.6	11.7	6.5	1.1	-5.7
3	1982	-7.2	-4.0	1.1	4.1	9.4	12.5	17.4	17.0	12.3	7.6	4.5	0.3
4	1983	0.7	-3.8	-0.1	4.0	10.2	14.0	18.0	17.8	12.4	7.5	1.2	-1.1
5	1984	-3.0	-1.7	-2.0	5.3	10.9	13.3	15.3	16.4	10.6	8.9	4.3	0.8
6	1985	-9.0	-11.6	-1.7	1.6	9.0	13.6	15.9	15.4	10.3	8.0	0.3	-4.3

	date	temp
	<date>	<dbl>
1	1980-01-01	-4.7
2	1980-02-01	-6.2
3	1980-03-01	-3.1
4	1980-04-01	4.8
5	1980-05-01	7.8
6	1980-06-01	15.6